esmvalcore.io.xcube#

Access data using xcube.

Run the command esmvaltool config copy data-xcube-esacci.yml to update your configuration to use this module. This will create a file with the following content in your configuration directory:

Listing 20 Contents of data-xcube-esacci.yml#

# Read data from the ESA Climate Data Centre (ESA CCI) using xcube.
# More information available at
# https://xcube.readthedocs.io/en/latest/dataaccess.html#esa-climate-data-centre-esa-cci-cciodp-ccizarr-esa-cci-kc.
projects:
  ESACCI:
    data:
      ccizarr:
        type: "esmvalcore.io.xcube.XCubeDataSource"
        data_store_id: "ccizarr"
        priority: 1
        values: &values
          # Use this to define the mapping between the short_name used by
          # ESMValCore and the variable name in the source dataset.
          short_name:
            prw: tcwv
      esa-cci-kc:
        type: "esmvalcore.io.xcube.XCubeDataSource"
        data_store_id: "esa-cci-kc"
        priority: 2
        values: *values
      cciodp:
        type: "esmvalcore.io.xcube.XCubeDataSource"
        data_store_id: "cciodp"
        priority: 3
        values: *values

Classes:

`XCubeDataSource`(name, project, priority, ...)	Data source for finding files on a local filesystem.
`XCubeDataset`(name, facets, store, ...)	A dataset that can be used to load data found using xcube.

class esmvalcore.io.xcube.XCubeDataSource(name: str, project: str, priority: int, data_store_id: str, values: dict[str, dict[str, str]] = <factory>, data_store_params: dict[str, ~typing.Any] = <factory>, open_params: dict[str, ~typing.Any] = <factory>)[source]#

Bases: DataSource

Data source for finding files on a local filesystem.

Attributes:

`data_store_id`	Name of the data store.
`data_store_params`	Parameters to use when creating the data store.
`debug_info`	A string containing debug information when no data is found.
`name`	A name identifying the data source.
`open_params`	Parameters to use when opening the data.
`priority`	The priority of the data source.
`project`	The project that the data source provides data for.
`values`	Mapping between the ESMValCore and xcube facet values.

Methods:

find_data(**facets)

Find data.

Parameters:

name (str)
project (str)
priority (int)
data_store_id (str)
values (dict[str, dict[str, str]])
data_store_params (dict[str, Any])
open_params (dict[str, Any])

data_store_id: str#

Name of the data store.

A list of available data stores can be found in the xcube documentation.

data_store_params: dict[str, Any]#: Parameters to use when creating the data store.

debug_info: str = ''#: A string containing debug information when no data is found.

find_data(**facets: FacetValue) → list[XCubeDataset][source]#

Find data.

Parameters:: **facets (FacetValue) – Find data matching these facets.
Returns:: A list of data elements that have been found.
Return type:: list[XCubeDataset]

name: str#: A name identifying the data source.

open_params: dict[str, Any]#: Parameters to use when opening the data.

priority: int#: The priority of the data source. Lower values have priority.

project: str#: The project that the data source provides data for.

values: dict[str, dict[str, str]]#: Mapping between the ESMValCore and xcube facet values.

class esmvalcore.io.xcube.XCubeDataset(name: str, facets: Facets, store: xcube.core.store.store.DataStore, open_params: dict[str, Any] = <factory>)[source]#

Bases: DataElement

A dataset that can be used to load data found using xcube.

Attributes:

`attributes`	Attributes are key-value pairs describing the data.
`facets`	Facets are key-value pairs that were used to find this data.
`name`	A unique name identifying the data.
`open_params`	Parameters to use when opening the data.
`store`	The store containing the data.

Methods:

`prepare`()	Prepare the data for access.
`to_iris`()	Load the data as Iris cubes.

Parameters:

name (str)
facets (Facets)
store (xcube.core.store.store.DataStore)
open_params (dict[str, Any])

property attributes: dict[str, Any]#: Attributes are key-value pairs describing the data.

facets: Facets#: Facets are key-value pairs that were used to find this data.

name: str#: A unique name identifying the data.

open_params: dict[str, Any]#: Parameters to use when opening the data.

prepare() → None[source]#

Prepare the data for access.

Return type:: None

store: xcube.core.store.store.DataStore#: The store containing the data.

to_iris() → iris.cube.CubeList[source]#

Load the data as Iris cubes.

Returns:: The loaded data.
Return type:: iris.cube.CubeList

esmvalcore.io.xcube#

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